Assessment of Machine Learning Detection of Environmental Enteropathy and Celiac Disease in Children.

ABSTRACT:

Importance

Duodenal biopsies from children with enteropathies associated with undernutrition, such as environmental enteropathy (EE) and celiac disease (CD), display significant histopathological overlap.

Objective

To develop a convolutional neural network (CNN) to enhance the detection of pathologic morphological features in diseased vs healthy duodenal tissue.

Design, setting, and participants

In this prospective diagnostic study, a CNN consisting of 4 convolutions, 1 fully connected layer, and 1 softmax layer was trained on duodenal biopsy images. Data were provided by 3 sites: Aga Khan University Hospital, Karachi, Pakistan; University Teaching Hospital, Lusaka, Zambia; and University of Virginia, Charlottesville. Duodenal biopsy slides from 102 children (10 with

SUBMITTER: Syed S 

PROVIDER: S-EPMC6575155 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature